Formulate and communicate the organizations data strategy, including data quality standards, data flow, and data security measures. Provides a standard common business vocabulary, expresses strategic data requirements, outlines high level integrated designs to meet these requirements. Define and implement data governance policies, procedures, and frameworks to ensure data integrity and compliance. Collaborate with stakeholders to align data strategy with business goals and objectives, document current and target state in the form of business process and data journey diagrams. Design and develop conceptual, logical, and physical data models that meet business requirements and align with the overall data strategy. Define data standards, naming conventions, and data classification guidelines. Ensure data models are scalable, efficient, and optimized for performance. Evaluate and select appropriate database technologies and solutions based on organizational needs and requirements. Design and oversee the implementation of data platforms, including relational databases, NoSQL databases, data warehousing, and Big Data solutions. Optimize database performance, ensure data security, and implement backup and recovery strategies. Design data integration solutions, including Extract, Transform, Load (ETL) processes and data pipelines, document source to target mappings. Collaborate with IT team and data experts to identify opportunities for data acquisition. Understand and follow data architecture patterns for various types of data systems, e.g. data lakehouse platforms, master data management systems, ML enriched data flows. Implement data profiling and data cleansing processes to identify and resolve data quality issues. Establish data quality standards and implement processes to measure, monitor, and improve data quality. Facilitate discussions and workshops to gather requirements and align data initiatives with business goals, prepare data inventory documentation. Communicate complex technical concepts effectively to both technical and non-technical stakeholders. Stay abreast of industry trends and emerging technologies in data management, analytics, and security. Evaluate and recommend new tools, technologies, and frameworks to enhance data architecture capabilities. Provide guidance and support to developers and other team members on data-related topics. Conduct knowledge sharing sessions and training programs to promote understanding and adoption of data architecture best practices. Requirements: Bachelors or Masters degree in Computer Science, Information Systems, or a related field. Proven experience as a Data Architect or in a similar role, ideally in a complex organizational setting. Strong understanding of data management principles, data modeling techniques, database design and data integration flows. Experience in developing and implementing data governance policies, procedures, and frameworks to ensure data integrity and compliance. Familiarity with industry best practices and emerging trends in data management and governance. Ability to design and develop conceptual, logical, and physical data models that meet business requirements and align with the overall data strategy. Strong understanding of data modeling best-practices, e.g. data normalization, denormalization, generalization, and performance optimization techniques. Expertise in working with various database technologies, such as relational databases (e.g., Oracle, SQL Server, MySQL) and NoSQL databases (e.g., MongoDB, Cassandra, DynamoDB). Knowledge of database management systems, data warehousing, data integration technologies, and Big Data solutions. Familiarity with cloud-based database, warehouse, and lakehouse platforms. Experience in designing and implementing data integration solutions, including Extract, Transform, Load (ETL) processes and data pipelines, understanding of data integration patterns and best practices. Understanding of Business Intelligence and data analytics requirements, optimization of data storage and processing for reporting needs. Excellent communication and presentation skills to effectively articulate complex technical concepts to both technical and non-technical stakeholders. Ability to collaborate with cross-functional teams, including business analysts, developers, and data scientists, to understand requirements and drive data-related initiatives. Strong analytical and problem-solving abilities to identify data-related issues, propose solutions, and make data-driven decisions. Familiarity with data profiling, data cleansing, data harmonization, and data quality assessment techniques. Knowledge of data security and privacy regulations, such as GDPR or CCPA, understanding of data encryption, access controls, and data masking techniques to ensure the security of sensitive data. Expertise in Google Cloud Platform (GCP), including BigQuery, Dataflow, and Cloud Storage. Professional certification in data management or related field would be advantageous.